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Record W4408254350 · doi:10.15332/22563067.10786

Procesos mentales y metapensamiento en el desarrollo cognitivo de los adolescentes

2025· article· es· W4408254350 on OpenAlexaboutno aff
Myriam Soraya Suárez Rojas, Maria del Pilar Salazar, Gina A. Castiblanco, A. Torres Muñoz

Bibliographic record

VenueDiversitas · 2025
Typearticle
Languagees
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPsychology

Abstract

fetched live from OpenAlex

Con el propósito de conocer los procesos mentales y la incidencia del metapensamiento en el desarrollo cognitivo de los adolescentes, se llevó a cabo una investigación con una muestra de 407 estudiantes de ocho instituciones educativas ubicadas en varias regiones del país. El objetivo de la investigación fue explicar las modalidades metacognitivas de la autorregulación del aprendizaje que están involucradas en el desarrollo cognitivo de los adolescentes. Para ello, se utilizó un diseño metodológico cuantitativo con un alcance descriptivo, el cual permitió determinar la concurrencia entre las categorías establecidas. Durante el procedimiento de categorización, se seleccionaron subcategorías que fueron abordadas mediante la implementación del instrumento estandarizado “Evaluación Cognitiva Montreal (MOCA)”, el cual facilitó la recolección y validación de los datos obtenidos. Entre los principales hallazgos, se identificó que la mayoría de los estudiantes manifiestan que, al momento de resolver un problema, razonan sobre sus conocimientos previos y experiencias pasadas que resultaron efectivas en su momento y que pueden ser aplicadas nuevamente en busca de una solución. Asimismo, destacan la importancia de buscar diversas alternativas y recursos como ruta para completar sus tareas.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.285
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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